The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD 

## [1] "2020-05-22"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide 

## [1] "5210817 (up from 5102424 yesterday: 2.12 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "338160 (up from 332924 yesterday: 1.57 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 6.49



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1600937 23790 1.51 95979 1277 1.35 6.00
Brazil 330890 20803 6.71 21048 1001 4.99 6.36
Russia 326448 8894 2.80 3249 150 4.84 1.00
United Kingdom 255544 3298 1.31 36475 351 0.97 14.27
Spain 234824 1787 0.77 28628 688 2.46 12.19
Italy 228658 652 0.29 32616 130 0.40 14.26
France 182015 64 0.04 28218 0 0.00 15.50
Germany 179710 689 0.38 8228 25 0.30 4.58
Turkey 154500 952 0.62 4276 27 0.64 2.77
Iran 131652 2311 1.79 7300 51 0.70 5.54
India 124794 6568 5.56 3726 142 3.96 2.99
Peru 111698 2929 2.69 3244 96 3.05 2.90
China 84081 18 0.02 4638 0 0.00 5.52
Canada 83947 1205 1.46 6360 93 1.48 7.58
Saudi Arabia 67719 2642 4.06 364 13 3.70 0.54
Mexico 62527 2960 4.97 6989 479 7.36 11.18
Chile 61857 4276 7.43 630 41 6.96 1.02
Belgium 56511 276 0.49 9212 26 0.28 16.30
Pakistan 50694 2603 5.41 1067 50 4.92 2.10
Netherlands 45088 188 0.42 5807 13 0.22 12.88
Qatar 40481 1830 4.73 19 2 11.76 0.05
Ecuador 35828 522 1.48 3056 117 3.98 8.53
Belarus 34303 932 2.79 190 5 2.70 0.55
Sweden 32809 637 1.98 3925 54 1.39 11.96
Switzerland 30707 13 0.04 1903 5 0.26 6.20
Singapore 30426 614 2.06 23 0 0.00 0.08
Bangladesh 30205 1694 5.94 432 24 5.88 1.43
Portugal 30200 288 0.96 1289 12 0.94 4.27
United Arab Emirates 27892 994 3.70 241 4 1.69 0.86
Ireland 24506 115 0.47 1592 9 0.57 6.50
Indonesia 20796 634 3.14 1326 48 3.76 6.38
Poland 20619 476 2.36 982 10 1.03 4.76
Ukraine 20148 442 2.24 588 9 1.55 2.92
South Africa 20125 988 5.16 397 28 7.59 1.97
Kuwait 19564 955 5.13 138 9 6.98 0.71
Colombia 19131 801 4.37 682 30 4.60 3.56
Romania 17712 127 0.72 1166 10 0.87 6.58
Israel 16690 7 0.04 279 0 0.00 1.67
Japan 16513 89 0.54 796 19 2.45 4.82
Austria 16436 32 0.20 635 2 0.32 3.86
Egypt 15786 783 5.22 707 11 1.58 4.48
Dominican Republic 13989 332 2.43 456 8 1.79 3.26
Philippines 13597 163 1.21 857 11 1.30 6.30
Denmark 11428 48 0.42 561 0 0.00 4.91
Korea, South 11165 23 0.21 266 2 0.76 2.38
Serbia 11024 105 0.96 237 0 0.00 2.15
Argentina 10649 718 7.23 433 17 4.09 4.07
Panama 10267 151 1.49 295 4 1.37 2.87
Afghanistan 9216 540 6.22 205 12 6.22 2.22
Czechia 8813 59 0.67 312 6 1.96 3.54
Bahrain 8414 240 2.94 12 0 0.00 0.14
Norway 8332 23 0.28 235 0 0.00 2.82
Kazakhstan 7919 685 9.47 35 0 0.00 0.44
Algeria 7918 190 2.46 582 7 1.22 7.35
Morocco 7332 121 1.68 197 1 0.51 2.69
Nigeria 7261 245 3.49 221 10 4.74 3.04
Malaysia 7137 78 1.10 115 1 0.88 1.61
Australia 7099 4 0.06 101 0 0.00 1.42
Moldova 6847 143 2.13 237 4 1.72 3.46
Oman 6794 424 6.66 34 3 9.68 0.50
Finland 6537 44 0.68 306 0 0.00 4.68
Ghana 6486 217 3.46 31 0 0.00 0.48
Armenia 5928 322 5.74 74 4 5.71 1.25
Bolivia 5579 392 7.56 230 15 6.98 4.12
Cameroon 4400 112 2.61 159 3 1.92 3.61
Luxembourg 3981 1 0.03 109 0 0.00 2.74
Iraq 3964 87 2.24 147 7 5.00 3.71
Azerbaijan 3855 106 2.83 46 2 4.55 1.19
Hungary 3678 37 1.02 476 3 0.63 12.94
Honduras 3477 273 8.52 167 11 7.05 4.80
Sudan 3378 240 7.65 137 16 13.22 4.06
Guinea 3067 0 0.00 19 1 5.56 0.62
Thailand 3037 0 0.00 56 0 0.00 1.84
Uzbekistan 3028 64 2.16 13 0 0.00 0.43
Senegal 2909 97 3.45 33 0 0.00 1.13
Greece 2874 21 0.74 169 1 0.60 5.88
Guatemala 2743 231 9.20 51 3 6.25 1.86
Tajikistan 2551 201 8.55 44 0 0.00 1.72
Bosnia and Herzegovina 2372 22 0.94 141 1 0.71 5.94
Bulgaria 2372 41 1.76 125 5 4.17 5.27
Cote d’Ivoire 2341 40 1.74 29 0 0.00 1.24
Djibouti 2270 223 10.89 10 0 0.00 0.44
Croatia 2243 6 0.27 99 2 2.06 4.41
Congo (Kinshasa) 1945 110 5.99 63 2 3.28 3.24
North Macedonia 1921 23 1.21 112 1 0.90 5.83
Cuba 1916 8 0.42 81 1 1.25 4.23
Estonia 1807 7 0.39 64 0 0.00 3.54
Iceland 1803 0 0.00 10 0 0.00 0.55
Gabon 1728 161 10.27 12 0 0.00 0.69
El Salvador 1725 85 5.18 33 0 0.00 1.91
Lithuania 1604 11 0.69 61 0 0.00 3.80
Somalia 1594 0 0.00 61 0 0.00 3.83
New Zealand 1504 0 0.00 21 0 0.00 1.40
Slovakia 1503 1 0.07 28 0 0.00 1.86
Slovenia 1468 0 0.00 106 0 0.00 7.22
Kyrgyzstan 1350 37 2.82 14 0 0.00 1.04
Maldives 1274 58 4.77 4 0 0.00 0.31
Kenya 1161 52 4.69 50 0 0.00 4.31
Guinea-Bissau 1114 5 0.45 6 0 0.00 0.54
Lebanon 1086 62 6.05 26 0 0.00 2.39
Sri Lanka 1068 13 1.23 9 0 0.00 0.84
Tunisia 1048 2 0.19 47 0 0.00 4.48
Latvia 1030 5 0.49 22 0 0.00 2.14
Kosovo 1004 1 0.10 29 0 0.00 2.89

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 358154 1696 0.48 28853 110 0.38 8.06 18410.72 1483.17 1 in 54
New Jersey 152579 993 0.66 10985 139 1.28 7.20 17178.08 1236.74 1 in 58
Illinois 105444 2756 2.68 4715 108 2.34 4.47 8321.14 372.09 1 in 120
Massachusetts 90889 805 0.89 6228 80 1.30 6.85 13078.49 896.18 1 in 76
California 90252 2221 2.52 3666 83 2.32 4.06 2284.15 92.78 1 in 438
Pennsylvania 70211 959 1.38 5010 141 2.90 7.14 5484.38 391.35 1 in 182
Michigan 53913 403 0.75 5158 29 0.57 9.57 5398.40 516.48 1 in 185
Texas 53539 486 0.92 1470 10 0.68 2.75 1846.43 50.70 1 in 542
Florida 49451 776 1.59 2190 46 2.15 4.43 2302.43 101.97 1 in 434
Maryland 44424 893 2.05 2207 48 2.22 4.97 7348.06 365.05 1 in 136
Georgia 41482 819 2.01 1808 33 1.86 4.36 3906.97 170.29 1 in 256
Connecticut 39640 432 1.10 3637 54 1.51 9.18 11118.32 1020.11 1 in 90
Louisiana 36925 421 1.15 2668 39 1.48 7.23 7942.92 573.91 1 in 126
Virginia 34950 813 2.38 1136 36 3.27 3.25 4094.65 133.09 1 in 244
Ohio 30794 627 2.08 1872 35 1.91 6.08 2634.42 160.15 1 in 380
Indiana 30409 473 1.58 1941 28 1.46 6.38 4516.94 288.32 1 in 221
Colorado 23487 296 1.28 1324 14 1.07 5.64 4078.50 229.91 1 in 245
North Carolina 22110 1598 7.79 775 47 6.46 3.51 2108.11 73.89 1 in 474
Tennessee 19394 433 2.28 315 2 0.64 1.62 2838.21 46.10 1 in 352
Washington 19265 148 0.77 1050 6 0.57 5.45 2529.91 137.89 1 in 395
Minnesota 19005 805 4.42 851 33 4.03 4.48 3369.90 150.90 1 in 297
Iowa 16492 322 1.99 424 14 3.41 2.57 5227.14 134.39 1 in 191
Arizona 15624 276 1.80 775 11 1.44 4.96 2051.77 101.77 1 in 487
Wisconsin 14396 511 3.68 496 9 1.85 3.45 2472.51 85.19 1 in 404
Rhode Island 13736 165 1.22 579 23 4.14 4.22 12966.31 546.56 1 in 77
Alabama 13670 382 2.87 541 12 2.27 3.96 2787.98 110.34 1 in 359
Mississippi 12625 403 3.30 595 15 2.59 4.71 4242.06 199.92 1 in 236
Missouri 11836 147 1.26 677 9 1.35 5.72 1928.50 110.31 1 in 519
Nebraska 11662 235 2.06 147 9 6.52 1.26 6028.72 75.99 1 in 166
South Carolina 9638 257 2.74 419 3 0.72 4.35 1871.92 81.38 1 in 534
Kansas 8909 284 3.29 205 1 0.49 2.30 3058.03 70.37 1 in 327
Delaware 8529 143 1.71 322 5 1.58 3.78 8758.80 330.68 1 in 114
Kentucky 8426 140 1.69 391 5 1.30 4.64 1885.99 87.52 1 in 530
Utah 8057 183 2.32 93 1 1.09 1.15 2513.13 29.01 1 in 398
District of Columbia 7893 105 1.35 418 6 1.46 5.30 11183.86 592.28 1 in 89
Nevada 7525 125 1.69 386 3 0.78 5.13 2443.06 125.32 1 in 409
New Mexico 6625 153 2.36 302 8 2.72 4.56 3159.53 144.03 1 in 317
Oklahoma 5849 169 2.98 307 3 0.99 5.25 1478.15 77.58 1 in 677
Arkansas 5612 154 2.82 113 3 2.73 2.01 1859.62 37.44 1 in 538
South Dakota 4356 179 4.29 50 2 4.17 1.15 4923.93 56.52 1 in 203
New Hampshire 4014 79 2.01 204 5 2.51 5.08 2952.10 150.03 1 in 339
Oregon 3864 47 1.23 147 2 1.38 3.80 916.13 34.85 1 in 1092
Puerto Rico 3030 117 4.02 126 0 0.00 4.16 948.74 39.45 1 in 1054
Idaho 2595 89 3.55 79 2 2.60 3.04 1448.05 44.08 1 in 691
North Dakota 2317 88 3.95 52 1 1.96 2.24 3040.44 68.24 1 in 329
Maine 1948 71 3.78 75 2 2.74 3.85 1449.18 55.79 1 in 690
West Virginia 1705 112 7.03 72 2 2.86 4.22 954.03 40.29 1 in 1048
Vermont 952 2 0.21 54 0 0.00 5.67 1525.67 86.54 1 in 655
Wyoming 803 2 0.25 12 0 0.00 1.49 1387.45 20.73 1 in 721
Hawaii 642 -5 -0.77 17 0 0.00 2.65 453.43 12.01 1 in 2205
Montana 479 0 0.00 16 0 0.00 3.34 448.18 14.97 1 in 2231
Alaska 403 2 0.50 10 0 0.00 2.48 550.89 13.67 1 in 1815

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 1600793 358154 22.37 82287.92
New Jersey 555314 152579 27.48 62519.94
Illinois 697133 105444 15.13 55014.43
Massachusetts 511644 90889 17.76 73623.11
California 1466773 90252 6.15 37122.01
Pennsylvania 379001 70211 18.53 29604.85
Michigan 471784 53913 11.43 47240.49
Texas 720928 53539 7.43 24863.12
Florida 835496 49451 5.92 38900.56
Maryland 227902 44424 19.49 37696.67
Georgia 427249 41482 9.71 40240.37
Connecticut 202328 39640 19.59 56749.43
Louisiana 311808 36925 11.84 67072.88
Virginia 225175 34950 15.52 26380.94
Ohio 307800 30794 10.00 26332.22
Indiana 208561 30409 14.58 30979.53
Colorado 142225 23487 16.51 24697.26
North Carolina 303224 22110 7.29 28911.29
Tennessee 361016 19394 5.37 52832.84
Washington 302927 19265 6.36 39780.86
Minnesota 180971 19005 10.50 32089.15
Iowa 120250 16492 13.71 38113.26
Arizona 176003 15624 8.88 23113.00
Wisconsin 187099 14396 7.69 32134.16
Rhode Island 127139 13736 10.80 120014.80
Alabama 177768 13670 7.69 36255.62
Mississippi 137973 12625 9.15 46359.57
Missouri 172946 11836 6.84 28178.90
Nebraska 78419 11662 14.87 40539.02
South Carolina 150023 9638 6.42 29137.96
Kansas 76434 8909 11.66 26236.10
Delaware 48986 8529 17.41 50305.82
Kentucky 166240 8426 5.07 37209.53
Utah 186834 8057 4.31 58277.12
District of Columbia 42993 7893 18.36 60918.26
Nevada 99941 7525 7.53 32446.73
New Mexico 152767 6625 4.34 72856.20
Oklahoma 153167 5849 3.82 38708.14
Arkansas 103047 5612 5.45 34146.12
South Dakota 32344 4356 13.47 36560.98
New Hampshire 55100 4014 7.28 40523.32
Oregon 107839 3864 3.58 25567.98
Puerto Rico 3030 3030 100.00 948.74
Idaho 39595 2595 6.55 22094.62
North Dakota 62830 2317 3.69 82447.36
Maine 37398 1948 5.21 27821.50
West Virginia 84829 1705 2.01 47466.16
Vermont 25733 952 3.70 41239.51
Wyoming 19424 803 4.13 33561.47
Hawaii 47985 642 1.34 33890.78
Montana 31857 479 1.50 29806.94
Alaska 41446 403 0.97 56655.43

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 44582 2940 7.06 12583 28.22 30482 1517 63 4.33 3.40
Tamil Nadu 14753 786 5.63 7128 48.32 7526 99 4 4.21 0.67
Gujarat 13273 363 2.81 5880 44.30 6591 802 29 3.75 6.04
Delhi 12319 660 5.66 5897 47.87 6214 208 14 7.22 1.69
Rajasthan 6494 267 4.29 3680 56.67 2661 153 2 1.32 2.36
Madhya Pradesh 6170 189 3.16 3089 50.06 2809 272 1 0.37 4.41
Uttar Pradesh 5735 220 3.99 3324 57.96 2259 152 14 10.14 2.65
West Bengal 3332 135 4.22 1221 36.64 1846 265 6 2.32 7.95
Andhra Pradesh 2667 62 2.38 1731 64.90 881 55 1 1.85 2.06
Bihar 2166 179 9.01 629 29.04 1526 11 2 22.22 0.51
Punjab 2029 1 0.05 1847 91.03 143 39 0 0.00 1.92
State Unassigned 1899 279 17.22 0 0.00 1899 0 0 NaN 0.00
Telangana 1761 62 3.65 1043 59.23 670 48 3 6.67 2.73
Karnataka 1743 138 8.60 597 34.25 1104 41 0 0.00 2.35
Jammu and Kashmir 1489 40 2.76 720 48.35 749 20 0 0.00 1.34
Odisha 1189 86 7.80 436 36.67 746 7 0 0.00 0.59
Haryana 1067 36 3.49 706 66.17 345 16 2 14.29 1.50
Kerala 733 42 6.08 512 69.85 216 5 1 25.00 0.68
Jharkhand 323 15 4.87 136 42.11 184 3 0 0.00 0.93
Assam 260 49 23.22 55 21.15 198 4 0 0.00 1.54
Chandigarh 219 1 0.46 178 81.28 38 3 0 0.00 1.37
Tripura 175 0 0.00 152 86.86 23 0 0 NaN 0.00
Chhattisgarh 172 40 30.30 62 36.05 110 0 0 NaN 0.00
Himachal Pradesh 168 16 10.53 55 32.74 106 4 0 0.00 2.38
Uttarakhand 153 7 4.79 53 34.64 99 1 0 0.00 0.65
Goa 54 2 3.85 7 12.96 47 0 0 NaN 0.00
Ladakh 46 2 4.55 43 93.48 3 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Manipur 26 1 4.00 2 7.69 24 0 0 NaN 0.00
Puducherry 26 3 13.04 10 38.46 16 0 0 NaN 0.00
Meghalaya 14 0 0.00 12 85.71 1 1 0 0.00 7.14
Arunachal Pradesh 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Mizoram 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN
Nagaland 0 0 NaN 0 NaN 0 0 0 NaN NaN
Sikkim 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 641593 86384 293 0.34 13.46 4028 207 25933 15784 18.27
Piemonte 276633 30077 87 0.29 10.87 1414 79 8452 3757 12.49
Emilia-Romagna 282857 27470 53 0.19 9.71 552 89 4730 4037 14.70
Veneto 559933 19059 21 0.11 3.40 215 12 3023 1854 9.73
Toscana 222505 10035 35 0.35 4.51 162 42 1786 1009 10.05
Liguria 89529 9389 45 0.48 10.49 269 19 1908 1407 14.99
Lazio 227090 7589 31 0.41 3.34 1111 67 3635 669 8.82
Marche 93549 6697 8 0.12 7.16 101 15 1768 990 14.78
Campania 161825 4733 10 0.21 2.92 312 9 1292 404 8.54
Puglia 99702 4440 27 0.61 4.45 233 17 1838 482 10.86
P.A. Trento 76001 4388 10 0.23 5.77 32 4 607 455 10.37
Sicilia 129431 3421 4 0.12 2.64 103 10 1519 268 7.83
Friuli Venezia Giulia 114062 3227 12 0.37 2.83 68 2 485 325 10.07
Abruzzo 63956 3220 8 0.25 5.03 157 4 1179 394 12.24
P.A. Bolzano 58188 2590 3 0.12 4.45 34 5 224 291 11.24
Umbria 61696 1429 0 0.00 2.32 16 2 59 74 5.18
Sardegna 48189 1356 0 0.00 2.81 58 6 306 128 9.44
Valle d’Aosta 13531 1177 1 0.09 8.70 22 2 43 143 12.15
Calabria 60847 1157 1 0.09 1.90 47 1 302 96 8.30
Molise 12616 426 3 0.71 3.38 8 2 184 22 5.16
Basilicata 25045 394 0 0.00 1.57 15 1 49 27 6.85

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 46150 646 1.42 3866 65 1.71 8.38 5405.45 452.82 1 in 185
Ontario 26085 490 1.91 2129 23 1.09 8.16 1773.06 144.71 1 in 564
Alberta 6800 32 0.47 134 2 1.52 1.97 1540.85 30.36 1 in 649
British Columbia 2507 28 1.13 155 3 1.97 6.18 490.52 30.33 1 in 2039
Nova Scotia 1048 2 0.19 58 0 0.00 5.53 1072.17 59.34 1 in 933
Saskatchewan 627 5 0.80 7 0 0.00 1.12 530.61 5.92 1 in 1885
Manitoba 292 2 0.69 7 0 0.00 2.40 211.98 5.08 1 in 4718
Newfoundland and Labrador 260 0 0.00 3 0 0.00 1.15 498.69 5.75 1 in 2005
New Brunswick 121 0 0.00 0 0 NaN 0.00 155.13 0.00 1 in 6446
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1591 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1065 4 0.38
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 788 7 0.89
Shanghai 667 7 1.05
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 563 3 0.53
Fujian 356 1 0.28
Hebei 328 6 1.83
Shaanxi 308 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 217 1 0.46
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 154 2 1.30
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 4892.84 293.33 1 in 204
Brazil 1580.94 100.56 1 in 633
Russia 2259.16 22.48 1 in 443
United Kingdom 3846.24 548.99 1 in 260
Spain 5032.66 613.54 1 in 199
Italy 3780.72 539.29 1 in 264
France 2717.05 421.23 1 in 368
Germany 2170.67 99.38 1 in 461
Turkey 1911.89 52.91 1 in 523
Iran 1622.13 89.95 1 in 616
India 93.20 2.78 1 in 10730
Peru 3472.12 100.84 1 in 288
China 60.66 3.35 1 in 16484
Canada 2233.23 169.19 1 in 448
Saudi Arabia 2055.83 11.05 1 in 486
Mexico 483.96 54.09 1 in 2066
Chile 3426.98 34.90 1 in 292
Belgium 4957.11 808.07 1 in 202
Pakistan 257.33 5.42 1 in 3886
Netherlands 2624.45 338.01 1 in 381

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 196484 21086 10.73
Cook Illinois 68949 3187 4.62
Los Angeles California 43070 2053 4.77
Nassau New York 39608 2082 5.26
Suffolk New York 38672 1814 4.69
Westchester New York 32767 1319 4.03
Philadelphia Pennsylvania 21009 1221 5.81
Middlesex Massachusetts 20085 1496 7.45
Wayne Michigan 19602 2323 11.85
Hudson New Jersey 18880 1134 6.01
Bergen New Jersey 17653 1515 8.58
Suffolk Massachusetts 17180 818 4.76
Essex New Jersey 17014 1585 9.32
Miami-Dade Florida 16522 614 3.72
Passaic New Jersey 15604 881 5.65
Union New Jersey 15191 1018 6.70
Middlesex New Jersey 15165 935 6.17
Fairfield Connecticut 14889 1195 8.03
Essex Massachusetts 13221 842 6.37
Prince George’s Maryland 13077 477 3.65
Rockland New York 12905 611 4.73
New Haven Connecticut 10756 888 8.26
Harris Texas 10526 217 2.06
Providence Rhode Island 10320 0 0.00
Orange New York 10142 428 4.22
Worcester Massachusetts 10101 652 6.45
Hartford Connecticut 9463 1155 12.21
Montgomery Maryland 9432 540 5.73
Marion Indiana 8928 528 5.91
Fairfax Virginia 8734 321 3.68
Dallas Texas 8477 207 2.44
Ocean New Jersey 8285 678 8.18
Oakland Michigan 8131 944 11.61
Maricopa Arizona 7950 368 4.63
District of Columbia District of Columbia 7893 418 5.30
Norfolk Massachusetts 7724 771 9.98
Monmouth New Jersey 7695 543 7.06
King Washington 7669 542 7.07
Plymouth Massachusetts 7424 492 6.63
Lake Illinois 7291 249 3.42
Jefferson Louisiana 7232 432 5.97
Orleans Louisiana 6944 500 7.20
DuPage Illinois 6744 337 5.00
Broward Florida 6580 286 4.35
Riverside California 6464 290 4.49
Macomb Michigan 6445 776 12.04
Montgomery Pennsylvania 6366 619 9.72
Bristol Massachusetts 6362 353 5.55
Hennepin Minnesota 6350 518 8.16
San Diego California 6315 241 3.82

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc